High-Dimensional Property Representation
Learn representations of high-dimensional electronic structures, such as DOS, to capture complex structure–property relationships.
Working backward from desired properties to viable chemical structures.
We use AI to generate material structures from target properties, leveraging high-dimensional information such as DOS to explore a broader materials space. We further extend inverse design to synthesis and processing, bridging the gap between material design and practical realization.
Learn representations of high-dimensional electronic structures, such as DOS, to capture complex structure–property relationships.
Generate and explore candidate material structures based on desired properties using AI-based inverse design models.
Jointly design material structures, synthesis routes, and processing conditions to bridge the gap between material design and experimental realization.